Factors associated with satisfaction and perceived helpfulness of mental healthcare: a World Mental Health Surveys report

BACKGROUND

Mental health service providers are increasingly interested in patient perspectives. We examined rates and predictors of patient-reported satisfaction and perceived helpfulness in a cross-national general population survey of adults with 12-month DSM-IV disorders who saw a provider for help with their mental health.

METHODS

Data were obtained from epidemiological surveys in the World Mental Health Survey Initiative. Respondents were asked about satisfaction with treatments received from up to 11 different types of providers (very satisfied, satisfied, neither satisfied nor dissatisfied, somewhat dissatisfied, very dissatisfied) and helpfulness of the provider (a lot, some, a little, not at all). We modelled predictors of satisfaction and helpfulness using a dataset of patient-provider observations (n = 5,248).

RESULTS

Most treatment was provided by general medical providers (37.4%), psychiatrists (18.4%) and psychologists (12.7%). Most patients were satisfied or very satisfied (65.9-87.5%, across provider) and helped a lot or some (64.4-90.3%). Spiritual advisors and healers were most often rated satisfactory and helpful. Social workers in human services settings were rated lowest on both dimensions. Patients also reported comparatively low satisfaction with general medical doctors and psychiatrists/psychologists and found general medical doctors less helpful than other providers. Men and students reported lower levels of satisfaction than women and nonstudents. Respondents with high education reported higher satisfaction and helpfulness than those with lower education. Type of mental disorder was unrelated to satisfaction but in some cases (depression, bipolar spectrum disorder, social phobia) was associated with low perceived helpfulness. Insurance was unrelated to either satisfaction or perceived helpfulness but in some cases was associated with elevated perceived helpfulness for a given level of satisfaction.

CONCLUSIONS

Satisfaction with and perceived helpfulness of treatment varied as a function of type of provider, service setting, mental status, and socio-demographic variables. Invariably, caution is needed in combining data from multiple countries where there are cultural and service delivery variations. Even so, our findings underscore the utility of patient perspectives in treatment evaluation and may also be relevant in efforts to match patients to treatments.

Prospective association of attachment style with suicide attempts among US Army soldiers

BACKGROUND

Insecure attachment styles are associated with retrospectively reported suicide attempts (SAs). It is not known if attachment styles are prospectively associated with medically documented SAs.

METHODS

A representative sample of US Army soldiers entering service (n = 21 772) was surveyed and followed via administrative records for their first 48 months of service. Attachment style (secure, preoccupied, fearful, dismissing) was assessed at baseline. Administrative medical records identified SAs. Discrete-time survival analysis examined associations of attachment style with future SA during service, adjusting for time in service, socio-demographics, service-related variables, and mental health diagnosis (MH-Dx). We examined whether associations of attachment style with SA differed based on sex and MH-Dx.

RESULTS

In total, 253 respondents attempted suicide. Endorsed attachment styles included secure (46.8%), preoccupied (9.1%), fearful (15.7%), and dismissing (19.2%). Examined separately, insecure attachment styles were associated with increased odds of SA: preoccupied [OR 2.5 (95% CI 1.7-3.4)], fearful [OR 1.6 (95% CI 1.1-2.3)], dismissing [OR 1.8 (95% CI 1.3-2.6)]. Examining attachment styles simultaneously along with other covariates, preoccupied [OR 1.9 (95% CI 1.4-2.7)] and dismissing [OR 1.7 (95% CI 1.2-2.4)] remained significant. The dismissing attachment and MH-Dx interaction was significant. In stratified analyses, dismissing attachment was associated with SA only among soldiers without MH-Dx. Other interactions were non-significant. Soldiers endorsing any insecure attachment style had elevated SA risk across the first 48 months in service, particularly during the first 12 months.

CONCLUSIONS

Insecure attachment styles, particularly preoccupied and dismissing, are associated with increased future SA risk among soldiers. Elevated risk is most substantial during first year of service but persists through the first 48 months. Dismissing attachment may indicate risk specifically among soldiers not identified by the mental healthcare system.

Predicting Homelessness Among Transitioning U.S. Army Soldiers

INTRODUCTION

This study develops a practical method to triage Army transitioning service members (TSMs) at highest risk of homelessness to target a preventive intervention.

METHODS

The sample included 4,790 soldiers from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in 1 of 3 Army STARRS 2011-2014 baseline surveys followed by the third wave of the STARRS-LS online panel surveys (2020-2022). Two machine learning models were trained: a Stage-1 model that used administrative predictors and geospatial data available for all TSMs at discharge to identify high-risk TSMs for initial outreach; and a Stage-2 model estimated in the high-risk subsample that used self-reported survey data to help determine highest risk based on additional information collected from high-risk TSMs once they are contacted. The outcome in both models was homelessness within 12 months after leaving active service.

RESULTS

Twelve-month prevalence of post-transition homelessness was 5.0% (SE=0.5). The Stage-1 model identified 30% of high-risk TSMs who accounted for 52% of homelessness. The Stage-2 model identified 10% of all TSMs (i.e., 33% of high-risk TSMs) who accounted for 35% of all homelessness (i.e., 63% of the homeless among high-risk TSMs).

CONCLUSIONS

Machine learning can help target outreach and assessment of TSMs for homeless prevention interventions.

Estimated Average Treatment Effect of Psychiatric Hospitalization in Patients With Suicidal Behaviors: A Precision Treatment Analysis

Importance

Psychiatric hospitalization is the standard of care for patients presenting to an emergency department (ED) or urgent care (UC) with high suicide risk. However, the effect of hospitalization in reducing subsequent suicidal behaviors is poorly understood and likely heterogeneous.

Objectives

To estimate the association of psychiatric hospitalization with subsequent suicidal behaviors using observational data and develop a preliminary predictive analytics individualized treatment rule accounting for heterogeneity in this association across patients.

Design, Setting, and Participants

A machine learning analysis of retrospective data was conducted. All veterans presenting with suicidal ideation (SI) or suicide attempt (SA) from January 1, 2010, to December 31, 2015, were included. Data were analyzed from September 1, 2022, to March 10, 2023. Subgroups were defined by primary psychiatric diagnosis (nonaffective psychosis, bipolar disorder, major depressive disorder, and other) and suicidality (SI only, SA in past 2-7 days, and SA in past day). Models were trained in 70.0% of the training samples and tested in the remaining 30.0%.

Exposures

Psychiatric hospitalization vs nonhospitalization.

Main Outcomes and Measures

Fatal and nonfatal SAs within 12 months of ED/UC visits were identified in administrative records and the National Death Index. Baseline covariates were drawn from electronic health records and geospatial databases.

Results

Of 196 610 visits (90.3% men; median [IQR] age, 53 [41-59] years), 71.5% resulted in hospitalization. The 12-month SA risk was 11.9% with hospitalization and 12.0% with nonhospitalization (difference, -0.1%; 95% CI, -0.4% to 0.2%). In patients with SI only or SA in the past 2 to 7 days, most hospitalization was not associated with subsequent SAs. For patients with SA in the past day, hospitalization was associated with risk reductions ranging from -6.9% to -9.6% across diagnoses. Accounting for heterogeneity, hospitalization was associated with reduced risk of subsequent SAs in 28.1% of the patients and increased risk in 24.0%. An individualized treatment rule based on these associations may reduce SAs by 16.0% and hospitalizations by 13.0% compared with current rates.

Conclusions and Relevance

The findings of this study suggest that psychiatric hospitalization is associated with reduced average SA risk in the immediate aftermath of an SA but not after other recent SAs or SI only. Substantial heterogeneity exists in these associations across patients. An individualized treatment rule accounting for this heterogeneity could both reduce SAs and avert hospitalizations.

Toward personalized care for insomnia in the US Army: a machine learning model to predict response to cognitive behavioral therapy for insomnia

STUDY OBJECTIVES

The standard of care for military personnel with insomnia is cognitive behavioral therapy for insomnia (CBT-I). However, only a minority seeking insomnia treatment receive CBT-I, and little reliable guidance exists to identify those most likely to respond. As a step toward personalized care, we present results of a machine learning (ML) model to predict CBT-I response.

METHODS

Administrative data were examined for n=1,449 nondeployed US Army soldiers treated for insomnia with CBT-I who had moderate-severe baseline Insomnia Severity Index (ISI) scores and completed one or more follow-up ISIs 6-12 weeks after baseline. An ensemble ML model was developed in a 70% training sample to predict clinically significant ISI improvement (reduction of at least two standard deviations on the baseline ISI distribution). Predictors included a wide range of military administrative and baseline clinical variables. Model accuracy was evaluated in the remaining 30% test sample.

RESULTS

19.8% of patients had clinically significant ISI improvement. Model AU-ROC (SE) was 0.60 (0.03). The 20% of test sample patients with highest probabilities of improvement were twice as likely to have clinically significant improvement as the remaining 80% (36.5% versus 15.7%; χ21=9.2, p=.002). Nearly 85% of prediction accuracy was due to ten variables, the most important of which were baseline insomnia severity and baseline suicidal ideation.

CONCLUSIONS

Pending replication, the model could be used as part of a patient-centered decision-making process for insomnia treatment. Parallel models will be needed for alternative treatments before such a system is of optimal value.

Patterns, predictors, and patient-reported reasons for antidepressant discontinuation in the WHO World Mental Health Surveys

BACKGROUND

Despite their documented efficacy, substantial proportions of patients discontinue antidepressant medication (ADM) without a doctor's recommendation. The current report integrates data on patient-reported reasons into an investigation of patterns and predictors of ADM discontinuation.

METHODS

Face-to-face interviews with community samples from 13 countries (n = 30 697) in the World Mental Health (WMH) Surveys included n = 1890 respondents who used ADMs within the past 12 months.

RESULTS

10.9% of 12-month ADM users reported discontinuation-based on recommendation of the prescriber while 15.7% discontinued in the absence of prescriber recommendation. The main patient-reported reason for discontinuation was feeling better (46.6%), which was reported by a higher proportion of patients who discontinued within the first 2 weeks of treatment than later. Perceived ineffectiveness (18.5%), predisposing factors (e.g. fear of dependence) (20.0%), and enabling factors (e.g. inability to afford treatment cost) (5.0%) were much less commonly reported reasons. Discontinuation in the absence of prescriber recommendation was associated with low country income level, being employed, and having above average personal income. Age, prior history of psychotropic medication use, and being prescribed treatment from a psychiatrist rather than from a general medical practitioner, in comparison, were associated with a lower probability of this type of discontinuation. However, these predictors varied substantially depending on patient-reported reasons for discontinuation.

CONCLUSION

Dropping out early is not necessarily negative with almost half of individuals noting they felt better. The study underscores the diverse reasons given for dropping out and the need to evaluate how and whether dropping out influences short- or long-term functioning.

Internet-delivered cognitive behavior therapy versus treatment as usual for anxiety and depression among Latin American university students: A randomized clinical trial

OBJECTIVE

Untreated mental disorders are important among low- and middle-income country (LMIC) university students in Latin America, where barriers to treatment are high. Scalable interventions are needed. This study compared transdiagnostic self-guided and guided internet-delivered cognitive behavioral therapy (i-CBT) with treatment as usual (TAU) for clinically significant anxiety and depression among undergraduates in Colombia and Mexico.

METHOD

1,319 anxious, as determined by the Generalized Anxiety Disorder-7 (GAD-7) = 10+ and/or depressed, as determined by the Patient Health Questionnaire-9 (PHQ-9) = 10+, undergraduates (mean [SD] age = 21.4 [3.2]); 78.7% female; 55.9% first-generation university student) from seven universities in Colombia and Mexico were randomized to culturally adapted versions of self-guided i-CBT (n = 439), guided i-CBT (n = 445), or treatment as usual (TAU; n = 435). All randomized participants were reassessed 3 months after randomization. The primary outcome was remission of both anxiety (GAD-7 = 0-4) and depression (PHQ-9 = 0-4). We hypothesized that remission would be higher with guided i-CBT than with the other interventions.

RESULTS

Intent-to-treat analysis found significantly higher adjusted (for university and loss to follow-up) remission rates (ARD) among participants randomized to guided i-CBT than either self-guided i-CBT (ARD = 13.1%, χ12 = 10.4, p = .001) or TAU (ARD = 11.2%, χ12 = 8.4, p = .004), but no significant difference between self-guided i-CBT and TAU (ARD = -1.9%, χ12 = 0.2, p = .63). Per-protocol sensitivity analyses and analyses of dimensional outcomes yielded similar results.

CONCLUSIONS

Significant reductions in anxiety and depression among LMIC university students could be achieved with guided i-CBT, although further research is needed to determine which students would most likely benefit from this intervention. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Optimism, Sociability, and the Risk of Future Suicide Attempt among U.S. Army Soldiers

INTRODUCTION

Most research on suicide attempts among U.S. service members has been focused on risk factors that occur during service. There is an important gap in our understanding of premilitary factors, such as personality characteristics, that may be associated with future suicide attempt risk during service. Of particular importance is identifying risk factors for the 1/3 of suicide attempters who never receive a mental health diagnosis (MH-Dx)-and therefore are not identified as having a mental health problem in the military healthcare system-prior to their suicide attempt.

MATERIALS AND METHODS

Using two components of the Army Study to Assess Risk and Resilience in Servicemembers, we examined the association of personality facets from the Tailored Adaptive Personality Assessment System, a computerized instrument administered prior to entering service, with medically documented suicide attempts during service. A 2010-2016 sample of historical administrative records from U.S. Regular Army enlisted soldiers with complete data on 11 commonly administered Tailored Adaptive Personality Assessment System facets was examined using a series of logistic regression analyses to identify the facets associated with future suicide attempt. Significant facets were then applied to data from a longitudinal cohort study of 11,288 soldiers surveyed upon entering basic combat training and followed via administrative records for their first 48 months of service. This research was approved by the Institutional Review Boards at the collaborating institutions.

RESULTS

Analysis of the historical administrative data (87.0% male, 61.6% White non-Hispanic), found that low Optimism (odds ratio (OR) = 1.2 [95% CI = 1.0-1.4]) and high/low (vs. moderate) Sociability (OR = 1.3 [95%CI = 1.1-1.6]) were associated with suicide attempt after adjusting for other univariable-significant facets and socio-demographic and service-related variables. When examined in the longitudinal survey cohort, low Optimism (OR = 1.7 [95% CI = 1.1-2.4]) and high/low (vs. moderate) Sociability (OR = 1.7 [95% CI = 1.1-2.5]) were still associated with increased odds of documented suicide attempt during service, even after adjusting for each other, socio-demographic and service-related variables, and medically documented MH-Dx. Mental health diagnosis had a significant two-way interaction with Optimism (F = 5.27, p = 0.0236) but not Sociability. Stratified analyses indicated that low Optimism was associated with suicide attempt among soldiers without, but not among those with, a MH-Dx. Interactions of Optimism and Sociability with gender were nonsignificant. In the full model, population attributable risk proportions for Optimism and Sociability were 15.0% and 18.9%, respectively. Optimism and Sociability were differentially associated with suicide attempt risk across time in service.

CONCLUSIONS

Optimism and Sociability, assessed prior to entering U.S. Army service, are consistently associated with future suicide attempt during service, even after adjusting for other important risk factors. While Sociability is equally associated with suicide attempt among those with and without a MH-Dx, Optimism is specifically associated with suicide attempt among soldiers not identified in the mental healthcare system. Risk differences across time in service suggest that Optimism and Sociability interact with stressors and contextual factors in particular developmental and Army career phases.

A practical risk calculator for suicidal behavior among transitioning U.S. Army soldiers: results from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS)

BACKGROUND

Risk of suicide-related behaviors is elevated among military personnel transitioning to civilian life. An earlier report showed that high-risk U.S. Army soldiers could be identified shortly before this transition with a machine learning model that included predictors from administrative systems, self-report surveys, and geospatial data. Based on this result, a Veterans Affairs and Army initiative was launched to evaluate a suicide-prevention intervention for high-risk transitioning soldiers. To make targeting practical, though, a streamlined model and risk calculator were needed that used only a short series of self-report survey questions.

METHODS

We revised the original model in a sample of n = 8335 observations from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in one of three Army STARRS 2011-2014 baseline surveys while in service and in one or more subsequent panel surveys (LS1: 2016-2018, LS2: 2018-2019) after leaving service. We trained ensemble machine learning models with constrained numbers of item-level survey predictors in a 70% training sample. The outcome was self-reported post-transition suicide attempts (SA). The models were validated in the 30% test sample.

RESULTS

Twelve-month post-transition SA prevalence was 1.0% (s.e. = 0.1). The best constrained model, with only 17 predictors, had a test sample ROC-AUC of 0.85 (s.e. = 0.03). The 10-30% of respondents with the highest predicted risk included 44.9-92.5% of 12-month SAs.

CONCLUSIONS

An accurate SA risk calculator based on a short self-report survey can target transitioning soldiers shortly before leaving service for intervention to prevent post-transition SA.

Stressful Life Events and Risk of Homelessness After Active Duty: An Assessment of Risk and Resilience Among Servicemembers

OBJECTIVES

The transition from military to civilian life may present increased exposure to various stressful life events (SLEs) that can increase the risk of homelessness (eg, loss of employment, dissolution of romantic relationships). We assessed the extent to which exposure to SLEs occurring proximal to US Army soldier transitions out of active duty was associated with risk of homelessness.

METHODS

A total of 16 589 respondents who were no longer on active duty but participated while on active duty during 2011-2014 baseline surveys completed follow-up surveys during 2016-2018 and 2018-2019. The follow-up surveys assessed SLEs and homelessness occurring in the past 12 months. We used modified Poisson regression models to evaluate how much differential SLE exposure and effects explained the aggregate association of a risk index with homelessness among a sample of 6837 respondents, weighted to represent the full sample.

RESULTS

More than half (n = 3510, 52.8%) of respondents reported experiencing any SLEs in the past 12 months. Most (60.5%) of the difference in prevalence of homelessness among respondents defined as being at high risk of homelessness (vs lower risk) was explained by differential exposure to, and/or effects of, these SLEs. Personal betrayal by a loved one and economic problems played the largest roles in adjusted risk differences (0.045 and 0.074, respectively).

CONCLUSIONS

Homelessness might be reduced by gearing interventions toward soldiers at high risk of homelessness who are transitioning out of active duty to reduce exposure to and effects of modifiable SLEs on experiencing homelessness.

Prospective associations of emotion reactivity and risk behaviors with suicide attempts in US Army soldiers

BACKGROUND

Emotion reactivity and risk behaviors (ERRB) are transdiagnostic dimensions associated with suicide attempt (SA). ERRB patterns may identify individuals at increased risk of future SAs.

METHODS

A representative sample of US Army soldiers entering basic combat training (n = 21 772) was surveyed and followed via administrative records for their first 48 months of service. Latent profile analysis of baseline survey items assessing ERRB dimensions, including emotion reactivity, impulsivity, and risk-taking behaviors, identified distinct response patterns (classes). SAs were identified using administrative medical records. A discrete-time survival framework was used to examine associations of ERRB classes with subsequent SA during the first 48 months of service, adjusting for time in service, socio-demographic and service-related variables, and mental health diagnosis (MH-Dx). We examined whether associations of ERRB classes with SA differed by year of service and for soldiers with and without a MH-Dx.

RESULTS

Of 21 772 respondents (86.2% male, 61.8% White non-Hispanic), 253 made a SA. Four ERRB classes were identified: 'Indirect Harming' (8.9% of soldiers), 'Impulsive' (19.3%), 'Risk-Taking' (16.3%), and 'Low ERRB' (55.6%). Compared to Low ERRB, Impulsive [OR 1.8 (95% CI 1.3-2.4)] and Risk-Taking [OR 1.6 (95% CI 1.1-2.2)] had higher odds of SA after adjusting for covariates. The ERRB class and MH-Dx interaction was non-significant. Within each class, SA risk varied across service time.

CONCLUSIONS

SA risk within the four identified ERRB classes varied across service time. Impulsive and Risk-Taking soldiers had increased risk of future SA. MH-Dx did not modify these associations, which may therefore help identify risk in those not yet receiving mental healthcare.

Age of onset and cumulative risk of mental disorders: a cross-national analysis of population surveys from 29 countries

BACKGROUND

Information on the frequency and timing of mental disorder onsets across the lifespan is of fundamental importance for public health planning. Broad, cross-national estimates of this information from coordinated general population surveys were last updated in 2007. We aimed to provide updated and improved estimates of age-of-onset distributions, lifetime prevalence, and morbid risk.

METHODS

In this cross-national analysis, we analysed data from respondents aged 18 years or older to the World Mental Health surveys, a coordinated series of cross-sectional, face-to-face community epidemiological surveys administered between 2001 and 2022. In the surveys, the WHO Composite International Diagnostic Interview, a fully structured psychiatric diagnostic interview, was used to assess age of onset, lifetime prevalence, and morbid risk of 13 DSM-IV mental disorders until age 75 years across surveys by sex. We did not assess ethnicity. The surveys were geographically clustered and weighted to adjust for selection probability, and standard errors of incidence rates and cumulative incidence curves were calculated using the jackknife repeated replications simulation method, taking weighting and geographical clustering of data into account.

FINDINGS

We included 156 331 respondents from 32 surveys in 29 countries, including 12 low-income and middle-income countries and 17 high-income countries, and including 85 308 (54·5%) female respondents and 71 023 (45·4%) male respondents. The lifetime prevalence of any mental disorder was 28·6% (95% CI 27·9-29·2) for male respondents and 29·8% (29·2-30·3) for female respondents. Morbid risk of any mental disorder by age 75 years was 46·4% (44·9-47·8) for male respondents and 53·1% (51·9-54·3) for female respondents. Conditional probabilities of first onset peaked at approximately age 15 years, with a median age of onset of 19 years (IQR 14-32) for male respondents and 20 years (12-36) for female respondents. The two most prevalent disorders were alcohol use disorder and major depressive disorder for male respondents and major depressive disorder and specific phobia for female respondents.

INTERPRETATION

By age 75 years, approximately half the population can expect to develop one or more of the 13 mental disorders considered in this Article. These disorders typically first emerge in childhood, adolescence, or young adulthood. Services should have the capacity to detect and treat common mental disorders promptly and to optimise care that suits people at these crucial parts of the life course.

FUNDING

None.

Design and field procedures for the clinical reappraisal of the Composite International Diagnostic Interview version 3.3 in Qatar's national mental health study

BACKGROUND

The Composite International Diagnostic Interview (CIDI) has been clinically reappraised in several studies conducted mainly in the US and Europe. This report describes the methodology used to conduct one of the Middle East's largest clinical reappraisal studies. The study was carried out in conjunction with the World Mental Health Qatar-the first national psychiatric epidemiological study of common mental disorders in the country. This study aimed to evaluate the diagnostic consistency of core modules of the newly translated and adapted Arabic version of the CIDI 5.0 against the independent clinical diagnoses based on the Structured Clinical Interview for DSM-5 (SCID-5).

METHODS

Telephone follow-up interviews were administered by trained clinicians using the latest research edition of the SCID for DSM-5. Telephone administered interviews were key in the data collection, as the study took place during the COVID-19 pandemic.

RESULTS

Overall, within 12 months, 485 interviews were completed. The response rate was 52%. Quality control monitoring documented excellent adherence of clinical interviews to the rating protocol.

CONCLUSIONS

The overall methods used in this study proved to be efficient and effective. For future research, instrument cultural adaptation within the cultural context is highly recommended.

A Precision Treatment Model for Internet-Delivered Cognitive Behavioral Therapy for Anxiety and Depression Among University Students: A Secondary Analysis of a Randomized Clinical Trial

Importance

Guided internet-delivered cognitive behavioral therapy (i-CBT) is a low-cost way to address high unmet need for anxiety and depression treatment. Scalability could be increased if some patients were helped as much by self-guided i-CBT as guided i-CBT.

Objective

To develop an individualized treatment rule using machine learning methods for guided i-CBT vs self-guided i-CBT based on a rich set of baseline predictors.

Design, Setting, and Participants

This prespecified secondary analysis of an assessor-blinded, multisite randomized clinical trial of guided i-CBT, self-guided i-CBT, and treatment as usual included students in Colombia and Mexico who were seeking treatment for anxiety (defined as a 7-item Generalized Anxiety Disorder [GAD-7] score of ≥10) and/or depression (defined as a 9-item Patient Health Questionnaire [PHQ-9] score of ≥10). Study recruitment was from March 1 to October 26, 2021. Initial data analysis was conducted from May 23 to October 26, 2022.

Interventions

Participants were randomized to a culturally adapted transdiagnostic i-CBT that was guided (n = 445), self-guided (n = 439), or treatment as usual (n = 435).

Main Outcomes and Measures

Remission of anxiety (GAD-7 scores of ≤4) and depression (PHQ-9 scores of ≤4) 3 months after baseline.

Results

The study included 1319 participants (mean [SD] age, 21.4 [3.2] years; 1038 women [78.7%]; 725 participants [55.0%] came from Mexico). A total of 1210 participants (91.7%) had significantly higher mean (SE) probabilities of joint remission of anxiety and depression with guided i-CBT (51.8% [3.0%]) than with self-guided i-CBT (37.8% [3.0%]; P = .003) or treatment as usual (40.0% [2.7%]; P = .001). The remaining 109 participants (8.3%) had low mean (SE) probabilities of joint remission of anxiety and depression across all groups (guided i-CBT: 24.5% [9.1%]; P = .007; self-guided i-CBT: 25.4% [8.8%]; P = .004; treatment as usual: 31.0% [9.4%]; P = .001). All participants with baseline anxiety had nonsignificantly higher mean (SE) probabilities of anxiety remission with guided i-CBT (62.7% [5.9%]) than the other 2 groups (self-guided i-CBT: 50.2% [6.2%]; P = .14; treatment as usual: 53.0% [6.0%]; P = .25). A total of 841 of 1177 participants (71.5%) with baseline depression had significantly higher mean (SE) probabilities of depression remission with guided i-CBT (61.5% [3.6%]) than the other 2 groups (self-guided i-CBT: 44.3% [3.7%]; P = .001; treatment as usual: 41.8% [3.2%]; P < .001). The other 336 participants (28.5%) with baseline depression had nonsignificantly higher mean (SE) probabilities of depression remission with self-guided i-CBT (54.4% [6.0%]) than guided i-CBT (39.8% [5.4%]; P = .07).

Conclusions and Relevance

Guided i-CBT yielded the highest probabilities of remission of anxiety and depression for most participants; however, these differences were nonsignificant for anxiety. Some participants had the highest probabilities of remission of depression with self-guided i-CBT. Information about this variation could be used to optimize allocation of guided and self-guided i-CBT in resource-constrained settings.

Trial Registration

ClinicalTrials.gov Identifier: NCT04780542.

Toward personalized care for insomnia in the US Army: development of a machine-learning model to predict response to pharmacotherapy

STUDY OBJECTIVES

Although many military personnel with insomnia are treated with prescription medication, little reliable guidance exists to identify patients most likely to respond. As a first step toward personalized care for insomnia, we present results of a machine-learning model to predict response to insomnia medication.

METHODS

The sample comprised n = 4,738 nondeployed US Army soldiers treated with insomnia medication and followed 6-12 weeks after initiating treatment. All patients had moderate-severe baseline scores on the Insomnia Severity Index (ISI) and completed 1 or more follow-up ISIs 6-12 weeks after baseline. An ensemble machine-learning model was developed in a 70% training sample to predict clinically significant ISI improvement, defined as reduction of at least 2 standard deviations on the baseline ISI distribution. Predictors included a wide range of military administrative and baseline clinical variables. Model accuracy was evaluated in the remaining 30% test sample.

RESULTS

21.3% of patients had clinically significant ISI improvement. Model test sample area under the receiver operating characteristic curve (standard error) was 0.63 (0.02). Among the 30% of patients with the highest predicted probabilities of improvement, 32.5.% had clinically significant symptom improvement vs 16.6% in the 70% sample predicted to be least likely to improve (χ21 = 37.1, P < .001). More than 75% of prediction accuracy was due to 10 variables, the most important of which was baseline insomnia severity.

CONCLUSIONS

Pending replication, the model could be used as part of a patient-centered decision-making process for insomnia treatment, but parallel models will be needed for alternative treatments before such a system is of optimal value.

CITATION

Gabbay FH, Wynn GH, Georg MW, et al. Toward personalized care for insomnia in the US Army: development of a machine-learning model to predict response to pharmacotherapy. J Clin Sleep Med. 2023;19(8):1399-1410.

Associations of vulnerability to stressful life events with suicide attempts after active duty among high-risk soldiers: results from the Study to Assess Risk and Resilience in Servicemembers-longitudinal study (STARRS-LS)

BACKGROUND

The transition from military service to civilian life is a high-risk period for suicide attempts (SAs). Although stressful life events (SLEs) faced by transitioning soldiers are thought to be implicated, systematic prospective evidence is lacking.

METHODS

Participants in the Army Study to Assess Risk and Resilience in Servicemembers (STARRS) completed baseline self-report surveys while on active duty in 2011-2014. Two self-report follow-up Longitudinal Surveys (LS1: 2016-2018; LS2: 2018-2019) were subsequently administered to probability subsamples of these baseline respondents. As detailed in a previous report, a SA risk index based on survey, administrative, and geospatial data collected before separation/deactivation identified 15% of the LS respondents who had separated/deactivated as being high-risk for self-reported post-separation/deactivation SAs. The current report presents an investigation of the extent to which self-reported SLEs occurring in the 12 months before each LS survey might have mediated/modified the association between this SA risk index and post-separation/deactivation SAs.

RESULTS

The 15% of respondents identified as high-risk had a significantly elevated prevalence of some post-separation/deactivation SLEs. In addition, the associations of some SLEs with SAs were significantly stronger among predicted high-risk than lower-risk respondents. Demographic rate decomposition showed that 59.5% (s.e. = 10.2) of the overall association between the predicted high-risk index and subsequent SAs was linked to these SLEs.

CONCLUSIONS

It might be possible to prevent a substantial proportion of post-separation/deactivation SAs by providing high-risk soldiers with targeted preventive interventions for exposure/vulnerability to commonly occurring SLEs.

Predictors of suicide attempt within 30 days of first medically documented major depression diagnosis in U.S. army soldiers with no prior suicidal ideation

BACKGROUND

Understanding mental health predictors of imminent suicide attempt (SA; within 30 days) among soldiers with depression and no prior suicide ideation (SI) can inform prevention and treatment. The current study aimed to identify sociodemographic and service-related characteristics and mental disorder predictors associated with imminent SA among U.S. Army soldiers following first documented major depression diagnosis (MDD) with no history of SI.

METHODS

In this case-control study using Army Study to Assess Risk and Resilience in Servicemembers (STARRS) administrative data, we identified 101,046 active-duty Regular Army enlisted soldiers (2010-2016) with medically-documented MDD and no prior SI (MDD/No-SI). We examined risk factors for SA within 30 days of first MDD/No-SI using logistic regression analyses, including socio-demographic/service-related characteristics and psychiatric diagnoses.

RESULTS

The 101,046 soldiers with documented MDD/No-SI were primarily male (78.0%), < 29 years old (63.9%), White (58.1%), high school-educated (74.5%), currently married (62.0%) and < 21 when first entering the Army (56.9%). Among soldiers with MDD/No-SI, 2,600 (2.6%) subsequently attempted suicide, 16.2% (n = 421) within 30 days (rate: 416.6/100,000). Our final multivariable model identified: Soldiers with less than high school education (χ²₃ = 11.21, OR = 1.5[95%CI = 1.2-1.9]); combat medics (χ²₂ = 8.95, OR = 1.5[95%CI = 1.1-2.2]); bipolar disorder (OR = 3.1[95%CI = 1.5-6.3]), traumatic stress (i.e., acute reaction to stress/not PTSD; OR = 2.6[95%CI = 1.4-4.8]), and "other" diagnosis (e.g., unspecified mental disorder: OR = 5.5[95%CI = 3.8-8.0]) diagnosed same day as MDD; and those with alcohol use disorder (OR = 1.4[95%CI = 1.0-1.8]) and somatoform/dissociative disorders (OR = 1.7[95%CI = 1.0-2.8]) diagnosed before MDD were more likely to attempt suicide within 30 days. Currently married soldiers (χ²₂ = 6.68, OR = 0.7[95%CI = 0.6-0.9]), those in service 10 + years (χ²₃ = 10.06, OR = 0.4[95%CI = 0.2-0.7]), and a sleep disorder diagnosed same day as MDD (OR = 0.3[95%CI = 0.1-0.9]) were less likely.

CONCLUSIONS

SA risk within 30 days following first MDD is more likely among soldiers with less education, combat medics, and bipolar disorder, traumatic stress, and "other" disorder the same day as MDD, and alcohol use disorder and somatoform/dissociative disorders before MDD. These factors identify imminent SA risk and can be indicators for early intervention.

Findings From the World Mental Health Surveys of Civil Violence Exposure and Its Association With Subsequent Onset and Persistence of Mental Disorders

Importance

Understanding the association of civil violence with mental disorders is important for developing effective postconflict recovery policies.

Objective

To estimate the association between exposure to civil violence and the subsequent onset and persistence of common mental disorders (in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition [DSM-IV]) in representative surveys of civilians from countries that have experienced civil violence since World War II.

Design, Setting, and Participants

This study used data from cross-sectional World Health Organization World Mental Health (WMH) surveys administered to households between February 5, 2001, and January 5, 2022, in 7 countries that experienced periods of civil violence after World War II (Argentina, Colombia, Lebanon, Nigeria, Northern Ireland, Peru, and South Africa). Data from respondents in other WMH surveys who immigrated from countries with civil violence in Africa and Latin America were also included. Representative samples comprised adults (aged ≥18 years) from eligible countries. Data analysis was performed from February 10 to 13, 2023.

Exposures

Exposure was defined as a self-report of having been a civilian in a war zone or region of terror. Related stressors (being displaced, witnessing atrocities, or being a combatant) were also assessed. Exposures occurred a median of 21 (IQR, 12-30) years before the interview.

Main Outcomes and Measures

The main outcome was the retrospectively reported lifetime prevalence and 12-month persistence (estimated by calculating 12-month prevalence among lifetime cases) of DSM-IV anxiety, mood, and externalizing (alcohol use, illicit drug use, or intermittent explosive) disorders.

Results

This study included 18 212 respondents from 7 countries. Of these individuals, 2096 reported that they were exposed to civil violence (56.5% were men; median age, 40 [IQR, 30-52] years) and 16 116 were not exposed (45.2% were men; median age, 35 [IQR, 26-48] years). Respondents who reported being exposed to civil violence had a significantly elevated onset risk of anxiety (risk ratio [RR], 1.8 [95% CI, 1.5-2.1]), mood (RR, 1.5 [95% CI, 1.3-1.7]), and externalizing (RR, 1.6 [95% CI, 1.3-1.9]) disorders. Combatants additionally had a significantly elevated onset risk of anxiety disorders (RR, 2.0 [95% CI, 1.3-3.1]) and refugees had an increased onset risk of mood (RR, 1.5 [95% CI, 1.1-2.0]) and externalizing (RR, 1.6 [95% CI, 1.0-2.4]) disorders. Elevated disorder onset risks persisted for more than 2 decades if conflicts persisted but not after either termination of hostilities or emigration. Persistence (ie, 12-month prevalence among respondents with lifetime prevalence of the disorder), in comparison, was generally not associated with exposure.

Conclusions

In this survey study of exposure to civil violence, exposure was associated with an elevated risk of mental disorders among civilians for many years after initial exposure. These findings suggest that policy makers should recognize these associations when projecting future mental disorder treatment needs in countries experiencing civil violence and among affected migrants.

Childhood adversities and mental disorders in first-year college students: results from the World Mental Health International College Student Initiative

BACKGROUND

This study investigates associations of several dimensions of childhood adversities (CAs) with lifetime mental disorders, 12-month disorder persistence, and impairment among incoming college students.

METHODS

Data come from the World Mental Health International College Student Initiative (WMH-ICS). Web-based surveys conducted in nine countries (n = 20 427) assessed lifetime and 12-month mental disorders, 12-month role impairment, and seven types of CAs occurring before the age of 18: parental psychopathology, emotional, physical, and sexual abuse, neglect, bullying victimization, and dating violence. Poisson regressions estimated associations using three dimensions of CA exposure: type, number, and frequency.

RESULTS

Overall, 75.8% of students reported exposure to at least one CA. In multivariate regression models, lifetime onset and 12-month mood, anxiety, and substance use disorders were all associated with either the type, number, or frequency of CAs. In contrast, none of these associations was significant when predicting disorder persistence. Of the three CA dimensions examined, only frequency was associated with severe role impairment among students with 12-month disorders. Population-attributable risk simulations suggest that 18.7-57.5% of 12-month disorders and 16.3% of severe role impairment among those with disorders were associated with these CAs.

CONCLUSION

CAs are associated with an elevated risk of onset and impairment among 12-month cases of diverse mental disorders but are not involved in disorder persistence. Future research on the associations of CAs with psychopathology should include fine-grained assessments of CA exposure and attempt to trace out modifiable intervention targets linked to mechanisms of associations with lifetime psychopathology and burden of 12-month mental disorders.

Development and evaluation of a risk algorithm predicting alcohol dependence after early onset of regular alcohol use

AIMS

Likelihood of alcohol dependence (AD) is increased among people who transition to greater levels of alcohol involvement at a younger age. Indicated interventions delivered early may be effective in reducing risk, but could be costly. One way to increase cost-effectiveness would be to develop a prediction model that targeted interventions to the subset of youth with early alcohol use who are at highest risk of subsequent AD.

DESIGN

A prediction model was developed for DSM-IV AD onset by age 25 years using an ensemble machine-learning algorithm known as 'Super Learner'. Shapley additive explanations (SHAP) assessed variable importance.

SETTING AND PARTICIPANTS

Respondents reporting early onset of regular alcohol use (i.e. by 17 years of age) who were aged 25 years or older at interview from 14 representative community surveys conducted in 13 countries as part of WHO's World Mental Health Surveys.

MEASUREMENTS

The primary outcome to be predicted was onset of life-time DSM-IV AD by age 25 as measured using the Composite International Diagnostic Interview, a fully structured diagnostic interview.

FINDINGS

AD prevalence by age 25 was 5.1% among the 10 687 individuals who reported drinking alcohol regularly by age 17. The prediction model achieved an external area under the curve [0.78; 95% confidence interval (CI) = 0.74-0.81] higher than any individual candidate risk model (0.73-0.77) and an area under the precision-recall curve of 0.22. Overall calibration was good [integrated calibration index (ICI) = 1.05%]; however, miscalibration was observed at the extreme ends of the distribution of predicted probabilities. Interventions provided to the 20% of people with highest risk would identify 49% of AD cases and require treating four people without AD to reach one with AD. Important predictors of increased risk included younger onset of alcohol use, males, higher cohort alcohol use and more mental disorders.

CONCLUSIONS

A risk algorithm can be created using data collected at the onset of regular alcohol use to target youth at highest risk of alcohol dependence by early adulthood. Important considerations remain for advancing the development and practical implementation of such models.

Determinants of effective treatment coverage for posttraumatic stress disorder: findings from the World Mental Health Surveys

BACKGROUND

Posttraumatic stress disorder (PTSD) is associated with significant morbidity, but efficacious pharmacotherapy and psychotherapy are available. Data from the World Mental Health Surveys were used to investigate extent and predictors of treatment coverage for PTSD in high-income countries (HICs) as well as in low- and middle-income countries (LMICs).

METHODS

Seventeen surveys were conducted across 15 countries (9 HICs, 6 LMICs) by the World Health Organization (WHO) World Mental Health Surveys. Of 35,012 respondents, 914 met DSM-IV criteria for 12-month PTSD. Components of treatment coverage analyzed were: (a) any mental health service utilization; (b) adequate pharmacotherapy; (c) adequate psychotherapy; and (d) effective treatment coverage. Regression models investigated predictors of treatment coverage.

RESULTS

12-month PTSD prevalence in trauma exposed individuals was 1.49 (S.E., 0.08). A total of 43.0% (S.E., 2.2) received any mental health services, with fewer receiving adequate pharmacotherapy (13.5%), adequate psychotherapy (17.2%), or effective treatment coverage (14.4%), and with all components of treatment coverage lower in LMICs than HICs. In a multivariable model having insurance (OR = 2.31, 95 CI 1.17, 4.57) and severity of symptoms (OR = .35, 95% CI 0.18, 0.70) were predictive of effective treatment coverage.

CONCLUSION

There is a clear need to improve pharmacotherapy and psychotherapy coverage for PTSD, particularly in those with mild symptoms, and especially in LMICs. Universal health care insurance can be expected to increase effective treatment coverage and therefore improve outcomes.

Antidepressant use in low- middle- and high-income countries: a World Mental Health Surveys report

BACKGROUND

The most common treatment for major depressive disorder (MDD) is antidepressant medication (ADM). Results are reported on frequency of ADM use, reasons for use, and perceived effectiveness of use in general population surveys across 20 countries.

METHODS

Face-to-face interviews with community samples totaling n = 49 919 respondents in the World Health Organization (WHO) World Mental Health (WMH) Surveys asked about ADM use anytime in the prior 12 months in conjunction with validated fully structured diagnostic interviews. Treatment questions were administered independently of diagnoses and asked of all respondents.

RESULTS

3.1% of respondents reported ADM use within the past 12 months. In high-income countries (HICs), depression (49.2%) and anxiety (36.4%) were the most common reasons for use. In low- and middle-income countries (LMICs), depression (38.4%) and sleep problems (31.9%) were the most common reasons for use. Prevalence of use was 2-4 times as high in HICs as LMICs across all examined diagnoses. Newer ADMs were proportionally used more often in HICs than LMICs. Across all conditions, ADMs were reported as very effective by 58.8% of users and somewhat effective by an additional 28.3% of users, with both proportions higher in LMICs than HICs. Neither ADM class nor reason for use was a significant predictor of perceived effectiveness.

CONCLUSION

ADMs are in widespread use and for a variety of conditions including but going beyond depression and anxiety. In a general population sample from multiple LMICs and HICs, ADMs were widely perceived to be either very or somewhat effective by the people who use them.

Evaluation of a Model to Target High-risk Psychiatric Inpatients for an Intensive Postdischarge Suicide Prevention Intervention

Importance

The months after psychiatric hospital discharge are a time of high risk for suicide. Intensive postdischarge case management, although potentially effective in suicide prevention, is likely to be cost-effective only if targeted at high-risk patients. A previously developed machine learning (ML) model showed that postdischarge suicides can be predicted from electronic health records and geospatial data, but it is unknown if prediction could be improved by adding additional information.

Objective

To determine whether model prediction could be improved by adding information extracted from clinical notes and public records.

Design, Setting, and Participants

Models were trained to predict suicides in the 12 months after Veterans Health Administration (VHA) short-term (less than 365 days) psychiatric hospitalizations between the beginning of 2010 and September 1, 2012 (299 050 hospitalizations, with 916 hospitalizations followed within 12 months by suicides) and tested in the hospitalizations from September 2, 2012, to December 31, 2013 (149 738 hospitalizations, with 393 hospitalizations followed within 12 months by suicides). Validation focused on net benefit across a range of plausible decision thresholds. Predictor importance was assessed with Shapley additive explanations (SHAP) values. Data were analyzed from January to August 2022.

Main Outcomes and Measures

Suicides were defined by the National Death Index. Base model predictors included VHA electronic health records and patient residential data. The expanded predictors came from natural language processing (NLP) of clinical notes and a social determinants of health (SDOH) public records database.

Results

The model included 448 788 unique hospitalizations. Net benefit over risk horizons between 3 and 12 months was generally highest for the model that included both NLP and SDOH predictors (area under the receiver operating characteristic curve range, 0.747-0.780; area under the precision recall curve relative to the suicide rate range, 3.87-5.75). NLP and SDOH predictors also had the highest predictor class-level SHAP values (proportional SHAP = 64.0% and 49.3%, respectively), although the single highest positive variable-level SHAP value was for a count of medications classified by the US Food and Drug Administration as increasing suicide risk prescribed the year before hospitalization (proportional SHAP = 15.0%).

Conclusions and Relevance

In this study, clinical notes and public records were found to improve ML model prediction of suicide after psychiatric hospitalization. The model had positive net benefit over 3-month to 12-month risk horizons for plausible decision thresholds. Although caution is needed in inferring causality based on predictor importance, several key predictors have potential intervention implications that should be investigated in future studies.

Non-suicidal self-injury among first-year college students and its association with mental disorders: results from the World Mental Health International College Student (WMH-ICS) initiative

BACKGROUND

Although non-suicidal self-injury (NSSI) is an issue of major concern to colleges worldwide, we lack detailed information about the epidemiology of NSSI among college students. The objectives of this study were to present the first cross-national data on the prevalence of NSSI and NSSI disorder among first-year college students and its association with mental disorders.

METHODS

Data come from a survey of the entering class in 24 colleges across nine countries participating in the World Mental Health International College Student (WMH-ICS) initiative assessed in web-based self-report surveys (20 842 first-year students). Using retrospective age-of-onset reports, we investigated time-ordered associations between NSSI and Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-IV) mood (major depressive and bipolar disorder), anxiety (generalized anxiety and panic disorder), and substance use disorders (alcohol and drug use disorder).

RESULTS

NSSI lifetime and 12-month prevalence were 17.7% and 8.4%. A positive screen of 12-month DSM-5 NSSI disorder was 2.3%. Of those with lifetime NSSI, 59.6% met the criteria for at least one mental disorder. Temporally primary lifetime mental disorders predicted subsequent onset of NSSI [median odds ratio (OR) 2.4], but these primary lifetime disorders did not consistently predict 12-month NSSI among respondents with lifetime NSSI. Conversely, even after controlling for pre-existing mental disorders, NSSI consistently predicted later onset of mental disorders (median OR 1.8) as well as 12-month persistence of mental disorders among students with a generalized anxiety disorder (OR 1.6) and bipolar disorder (OR 4.6).

CONCLUSIONS

NSSI is common among first-year college students and is a behavioral marker of various common mental disorders.

COVID-19 and common mental disorders among university students in South Africa

COVID-19 has had far-reaching economic, social and health consequences, with vulnerable groups disproportionally affected. Even before the COVID-19 pandemic, concern was expressed about university students’ mental health, with global data suggesting students are more vulnerable than the general population to mental disorders. Yet, it is unclear what the pandemic’s impact has been on the mental health of students in South Africa. We examined the impact of COVID-19 on first-year students at two universities in South Africa by analysing changes in the prevalence and age-of-onset of three common mental disorders (namely major depressive episode, generalised anxiety disorder, and suicidal ideation) before and during the pandemic, and comparing these to changes between 2015 and 2017. Our analysis of cross-sectional survey data collected in 2015, 2017 and 2020 shows no clear or consistent pattern of increases in prevalence of common mental disorders following the start of the pandemic. Lifetime prevalence rates of common mental disorders among students have been steadily increasing since 2015, and where increases before and during COVID-19 were observed, they are not consistently larger than increases between 2015 and 2020. No significant changes were observed in the 12-month prevalence of common mental disorders before and during COVID-19, except for an increase in prevalence of depression at one institution, and a decrease in suicidal ideation at the other. Findings suggest that in the context of ongoing adversity and disruptions on South African university campuses in recent years, COVID-19 may be just one more stressor local students face and that its impact on student mental health may not have been as marked in South Africa compared to other regions.

Perceived helpfulness of treatment for social anxiety disorder: findings from the WHO World Mental Health Surveys

PURPOSE

To investigate the prevalence and predictors of perceived helpfulness of treatment in persons with a history of DSM-IV social anxiety disorder (SAD), using a worldwide population-based sample.

METHODS

The World Health Organization World Mental Health Surveys is a coordinated series of community epidemiological surveys of non-institutionalized adults; 27 surveys in 24 countries (16 in high-income; 11 in low/middle-income countries; N = 117,856) included people with a lifetime history of treated SAD.

RESULTS

In respondents with lifetime SAD, approximately one in five ever obtained treatment. Among these (n = 1322), cumulative probability of receiving treatment they regarded as helpful after seeing up to seven professionals was 92.2%. However, only 30.2% persisted this long, resulting in 65.1% ever receiving treatment perceived as helpful. Perceiving treatment as helpful was more common in female respondents, those currently married, more highly educated, and treated in non-formal health-care settings. Persistence in seeking treatment for SAD was higher among those with shorter delays in seeking treatment, in those receiving medication from a mental health specialist, and those with more than two lifetime anxiety disorders.

CONCLUSIONS

The vast majority of individuals with SAD do not receive any treatment. Among those who do, the probability that people treated for SAD obtain treatment they consider helpful increases considerably if they persisted in help-seeking after earlier unhelpful treatments.

Prospective Associations of Military Discharge Characterization with Post-active Duty Suicide Attempts and Homelessness: Results from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS)

INTRODUCTION

Active duty service members transitioning to civilian life can experience significant readjustment stressors. Over the past two decades of the United States' longest sustained conflict, reducing transitioning veterans' suicidal behavior and homelessness became national priorities. However, it remains a significant challenge to identify which service members are at greatest risk of these post-active duty outcomes. Discharge characterization, which indicates the quality of an individual's military service and affects eligibility for benefits and services at the Department of Veterans Affairs, is a potentially important indicator of risk.

MATERIALS AND METHODS

This study used data from two self-report panel surveys of the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) (LS1: 2016-2018, n = 14,508; and LS2: 2018-2019, n = 12,156), which were administered to respondents who previously participated while on active duty in one of the three Army STARRS baseline self-report surveys (2011-2014): the New Soldier Study (NSS), a survey of soldiers entering basic training; All Army Study, a survey of active duty soldiers around the world; and the Pre-Post Deployment Study, a survey of soldiers before and after combat deployment. Human Subjects Committees of the participating institutions approved all recruitment, informed consent, and data collection protocols. We used modified Poisson regression models to prospectively examine the association of discharge characterization (honorable, general, "bad paper" [other than honorable, bad conduct, dishonorable], and uncharacterized [due to separation within the first 180 days of service]) with suicide attempt (subsample of n = 4334 observations) and homelessness (subsample of n = 6837 observations) among those no longer on active duty (i.e., separated or deactivated). Analyses controlled for other suicide attempt and homelessness risk factors using standardized risk indices that were previously developed using the LS survey data.

RESULTS

Twelve-month prevalence rates of self-reported suicide attempts and homelessness in the total pooled LS sample were 1.0% and 2.9%, respectively. While not associated with suicide attempt risk, discharge characterization was associated with homelessness after controlling for other risk factors. Compared to soldiers with an honorable discharge, those with a bad paper discharge had an increased risk of homelessness in the total sample (relative risk [RR] = 4.4 [95% CI = 2.3-8.4]), as well as within subsamples defined by which baseline survey respondents completed (NSS vs. All Army Study/Pre-Post Deployment Study), whether respondents had been separated (vs. deactivated), and how much time had elapsed since respondents were last on active duty.

CONCLUSIONS

There is a robust association between receiving a bad paper discharge and post-separation/deactivation homelessness. Policies that enhance transition assistance and access to mental healthcare for high-risk soldiers may aid in reducing post-separation/deactivation homelessness among those who do not receive an honorable discharge.

Childhood adversities and suicidal thoughts and behaviors among first-year college students: results from the WMH-ICS initiative

PURPOSE

To investigate the associations of childhood adversities (CAs) with lifetime onset and transitions across suicidal thoughts and behaviors (STB) among incoming college students.

METHODS

Web-based self-report surveys administered to 20,842 incoming college students from nine countries (response rate 45.6%) assessed lifetime suicidal ideation, plans and attempts along with seven CAs: parental psychopathology, three types of abuse (emotional, physical, sexual), neglect, bully victimization, and dating violence. Logistic regression estimated individual- and population-level associations using CA operationalizations for type, number, severity, and frequency.

RESULTS

Associations of CAs with lifetime ideation and the transition from ideation to plan were best explained by the exact number of CA types (OR range 1.32-52.30 for exactly two to seven CAs). Associations of CAs with a transition to attempts were best explained by the frequency of specific CA types (scaled 0-4). Attempts among ideators with a plan were significantly associated with all seven CAs (OR range 1.16-1.59) and associations remained significant in adjusted analyses with the frequency of sexual abuse (OR = 1.42), dating violence (OR = 1.29), physical abuse (OR = 1.17) and bully victimization (OR = 1.17). Attempts among ideators without plan were significantly associated with frequency of emotional abuse (OR = 1.29) and bully victimization (OR = 1.36), in both unadjusted and adjusted analyses. Population attributable risk simulations found 63% of ideation and 30-47% of STB transitions associated with CAs.

CONCLUSION

Early-life adversities represent a potentially important driver in explaining lifetime STB among incoming college students. Comprehensive intervention strategies that prevent or reduce the negative effects of CAs may reduce subsequent onset of STB.

Predicting Homelessness Among U.S. Army Soldiers No Longer on Active Duty

INTRODUCTION

The ability to predict and prevent homelessness has been an elusive goal. The purpose of this study was to develop a prediction model that identified U.S. Army soldiers at high risk of becoming homeless after transitioning to civilian life based on information available before the time of this transition.

METHODS

The prospective cohort study consisted of observations from 16,589 soldiers who were separated or deactivated from service and who had previously participated in 1 of 3 baseline surveys of the Army Study to Assess Risk and Resilience in Servicemembers in 2011-2014. A machine learning model was developed in a 70% training sample and evaluated in the remaining 30% test sample to predict self-reported homelessness in 1 of 2 Longitudinal Study surveys administered in 2016-2018 and 2018-2019. Predictors included survey, administrative, and geospatial variables available before separation/deactivation. Analysis was conducted in November 2020-May 2021.

RESULTS

The 12-month prevalence of homelessness was 2.9% (SE=0.2%) in the total Longitudinal Study sample. The area under the receiver operating characteristic curve in the test sample was 0.78 (SE=0.02) for homelessness. The 4 highest ventiles (top 20%) of predicted risk included 61% of respondents with homelessness. Self-reported lifetime histories of depression, trauma of having a loved one murdered, and post-traumatic stress disorder were the 3 strongest predictors of homelessness.

CONCLUSIONS

A prediction model for homelessness can accurately target soldiers for preventive intervention before transition to civilian life.

The Appalachia Mind Health Initiative (AMHI): a pragmatic randomized clinical trial of adjunctive internet-based cognitive behavior therapy for treating major depressive disorder among primary care patients

BACKGROUND

Major depressive disorder (MDD) is a leading cause of disease morbidity. Combined treatment with antidepressant medication (ADM) plus psychotherapy yields a much higher MDD remission rate than ADM only. But 77% of US MDD patients are nonetheless treated with ADM only despite strong patient preferences for psychotherapy. This mismatch is due at least in part to a combination of cost considerations and limited availability of psychotherapists, although stigma and reluctance of PCPs to refer patients for psychotherapy are also involved. Internet-based cognitive behaviorial therapy (i-CBT) addresses all of these problems.

METHODS

Enrolled patients (n = 3360) will be those who are beginning ADM-only treatment of MDD in primary care facilities throughout West Virginia, one of the poorest and most rural states in the country. Participating treatment providers and study staff at West Virginia University School of Medicine (WVU) will recruit patients and, after obtaining informed consent, administer a baseline self-report questionnaire (SRQ) and then randomize patients to 1 of 3 treatment arms with equal allocation: ADM only, ADM + self-guided i-CBT, and ADM + guided i-CBT. Follow-up SRQs will be administered 2, 4, 8, 13, 16, 26, 39, and 52 weeks after randomization. The trial has two primary objectives: to evaluate aggregate comparative treatment effects across the 3 arms and to estimate heterogeneity of treatment effects (HTE). The primary outcome will be episode remission based on a modified version of the patient-centered Remission from Depression Questionnaire (RDQ). The sample was powered to detect predictors of HTE that would increase the proportional remission rate by 20% by optimally assigning individuals as opposed to randomly assigning them into three treatment groups of equal size. Aggregate comparative treatment effects will be estimated using intent-to-treat analysis methods. Cumulative inverse probability weights will be used to deal with loss to follow-up. A wide range of self-report predictors of MDD heterogeneity of treatment effects based on previous studies will be included in the baseline SRQ. A state-of-the-art ensemble machine learning method will be used to estimate HTE.

DISCUSSION

The study is innovative in using a rich baseline assessment and in having a sample large enough to carry out a well-powered analysis of heterogeneity of treatment effects. We anticipate finding that self-guided and guided i-CBT will both improve outcomes compared to ADM only. We also anticipate finding that the comparative advantages of adding i-CBT to ADM will vary significantly across patients. We hope to develop a stable individualized treatment rule that will allow patients and treatment providers to improve aggregate treatment outcomes by deciding collaboratively when ADM treatment should be augmented with i-CBT.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04120285 . Registered on October 19, 2019.

Study protocol for pragmatic trials of Internet-delivered guided and unguided cognitive behavior therapy for treating depression and anxiety in university students of two Latin American countries: the Yo Puedo Sentirme Bien study

BACKGROUND

Major depressive disorder (MDD) and generalized anxiety disorder (GAD) are highly prevalent among university students and predict impaired college performance and later life role functioning. Yet most students do not receive treatment, especially in low-middle-income countries (LMICs). We aim to evaluate the effects of expanding treatment using scalable and inexpensive Internet-delivered transdiagnostic cognitive behavioral therapy (iCBT) among college students with symptoms of MDD and/or GAD in two LMICs in Latin America (Colombia and Mexico) and to investigate the feasibility of creating a precision treatment rule (PTR) to predict for whom iCBT is most effective.

METHODS

We will first carry out a multi-site randomized pragmatic clinical trial (N = 1500) of students seeking treatment at student mental health clinics in participating universities or responding to an email offering services. Students on wait lists for clinic services will be randomized to unguided iCBT (33%), guided iCBT (33%), and treatment as usual (TAU) (33%). iCBT will be provided immediately whereas TAU will be whenever a clinic appointment is available. Short-term aggregate effects will be assessed at 90 days and longer-term effects 12 months after randomization. We will use ensemble machine learning to predict heterogeneity of treatment effects of unguided versus guided iCBT versus TAU and develop a precision treatment rule (PTR) to optimize individual student outcome. We will then conduct a second and third trial with separate samples (n = 500 per arm), but with unequal allocation across two arms: 25% will be assigned to the treatment determined to yield optimal outcomes based on the PTR developed in the first trial (PTR for optimal short-term outcomes for Trial 2 and 12-month outcomes for Trial 3), whereas the remaining 75% will be assigned with equal allocation across all three treatment arms.

DISCUSSION

By collecting comprehensive baseline characteristics to evaluate heterogeneity of treatment effects, we will provide valuable and innovative information to optimize treatment effects and guide university mental health treatment planning. Such an effort could have enormous public-health implications for the region by increasing the reach of treatment, decreasing unmet need and clinic wait times, and serving as a model of evidence-based intervention planning and implementation.

TRIAL STATUS

IRB Approval of Protocol Version 1.0; June 3, 2020. Recruitment began on March 1, 2021. Recruitment is tentatively scheduled to be completed on May 30, 2024.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04780542 . First submission date: February 28, 2021.

Association of Premilitary Mental Health With Suicide Attempts During US Army Service

IMPORTANCE

Approximately one-third of US soldiers who attempt suicide have not received a mental health diagnosis (MH-Dx) before their suicide attempt (SA), yet little is known about risk factors for SA in those with no MH-Dx.

OBJECTIVE

To examine whether premilitary mental health is associated with medically documented SA among US Army soldiers who do not receive an MH-Dx before their SA.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used data from a representative survey of soldiers in the US Army entering basic combat training from April 1, 2011, to November 30, 2012, who were followed up via administrative records for the first 48 months of service. Analyses were conducted from April 5, 2021, to January 21, 2022. Regular Army enlisted soldiers (n = 21 772) recruited from 3 US Army installations during the first week of service who agreed to have their administrative records linked to their survey responses were included.

EXPOSURES

Preenlistment lifetime history of mental disorder, suicide ideation, SA, and nonsuicidal self-injury (NSSI) as reported during the baseline survey. Service-acquired MH-Dx and sociodemographic and service-related variables were identified using administrative records.

MAIN OUTCOMES AND MEASURES

Documented SAs were identified using administrative medical records. Using a discrete-time survival framework, linear splines examined the pattern of SA risk over the first 48 months of service. Logistic regression analysis examined associations of lifetime baseline survey variables with subsequent, medically documented SA among soldiers who did vs did not receive an MH-Dx during service. Models were adjusted for time in service and sociodemographic and service-related variables.

RESULTS

Of the 21 722 respondents (86.2% male, 20.4% Black, 61.8% White non-Hispanic), 253 made an SA in the first 48 months of service (male [75.4%]; Black [22.7%], White non-Hispanic [59.9%], or other race or ethnicity [17.4%]). Risk of SA peaked toward the end of the first year of service for both those who did and did not receive an MH-Dx during service. Of the 42.3% of individuals reporting at least 1 of the 4 baseline risk factors, 50.2% received an administrative MH-Dx during service vs 41.5% of those with none, and 1.6% had a documented SA vs 1.0% of those with none. Among individuals with no MH-Dx, medically documented SAs were associated with suicide ideation (odds ratio [OR], 2.2; 95% CI, 1.1-4.4), SA (OR, 11.3; 95% CI, 4.3-29.2), and NSSI (OR, 3.0; 95% CI, 1.3-6.8). For those who received an MH-Dx, medically documented SAs were associated with mental disorder (OR, 1.4; 95% CI, 1.0-1.9), SA (OR, 3.4; 95% CI, 2.1-5.6), and NSSI (OR, 1.8; 95% CI, 1.1-2.8). Interactions indicated the only explanatory variable that differed based on history of MH-Dx was preenlistment SA (χ21 = 4.7; P = .03), which had a larger OR among soldiers with no MH-Dx than among those with an MH-Dx.

CONCLUSIONS AND RELEVANCE

In this study, the period of greatest SA risk and baseline risk factors for SA were similar in soldiers with and without an MH-Dx. This finding suggests that knowledge of the time course and preenlistment mental health factors can equally aid in identifying SA risk in soldiers who do and do not receive an MH-Dx.

Patterns and correlates of patient-reported helpfulness of treatment for common mental and substance use disorders in the WHO World Mental Health Surveys

Patient-reported helpfulness of treatment is an important indicator of quality in patient-centered care. We examined its pathways and predictors among respondents to household surveys who reported ever receiving treatment for major depression, generalized anxiety disorder, social phobia, specific phobia, post-traumatic stress disorder, bipolar disorder, or alcohol use disorder. Data came from 30 community epidemiological surveys - 17 in high-income countries (HICs) and 13 in low- and middle-income countries (LMICs) - carried out as part of the World Health Organization (WHO)'s World Mental Health (WMH) Surveys. Respondents were asked whether treatment of each disorder was ever helpful and, if so, the number of professionals seen before receiving helpful treatment. Across all surveys and diagnostic categories, 26.1% of patients (N=10,035) reported being helped by the very first professional they saw. Persisting to a second professional after a first unhelpful treatment brought the cumulative probability of receiving helpful treatment to 51.2%. If patients persisted with up through eight professionals, the cumulative probability rose to 90.6%. However, only an estimated 22.8% of patients would have persisted in seeing these many professionals after repeatedly receiving treatments they considered not helpful. Although the proportion of individuals with disorders who sought treatment was higher and they were more persistent in HICs than LMICs, proportional helpfulness among treated cases was no different between HICs and LMICs. A wide range of predictors of perceived treatment helpfulness were found, some of them consistent across diagnostic categories and others unique to specific disorders. These results provide novel information about patient evaluations of treatment across diagnoses and countries varying in income level, and suggest that a critical issue in improving the quality of care for mental disorders should be fostering persistence in professional help-seeking if earlier treatments are not helpful.

ADHD Comorbidity Structure and Impairment: Results of the WHO World Mental Health Surveys International College Student Project (WMH-ICS)

OBJECTIVE

To examine the prevalence of ADHD and the association of comorbid disorders, and multivariate disorder classes with role impairment in college students.

METHOD

About 15,991 freshmen (24 colleges, 9 countries, WMH-ICS) (response rate = 45.6%) completed online WMH-CIDI-SC surveys for 6-month ADHD and six 12-month DSM-IV disorders. We examined multivariate disorder classes using latent class analysis (LCA) and simulated a population attributable risk proportions (PARPs) of ADHD-related impairment.

RESULTS

About 15.9% had ADHD, of which 58.4% had comorbidities. LCA classified ADHD respondents to pure (42.9%), internalizing (36.0%), bipolar comorbidities (11.3%), and externalizing disorder classes (9.8%). ADHD, comorbidities, and multivariate disorder classes independently predicted severe impairment. PARPs: eliminating ADHD hypothetically reduced severe impairment by 19.2%, 10.1% adjusted for comorbidities, 9.5% for multivariate disorder classes.

CONCLUSIONS

ADHD and comorbid disorders are common and impairing in college students. Personalized transdiagnostic interventions guided by multivariate disorder classes should be explored.

Estimated Prevalence of and Factors Associated With Clinically Significant Anxiety and Depression Among US Adults During the First Year of the COVID-19 Pandemic

IMPORTANCE

Claims of dramatic increases in clinically significant anxiety and depression early in the COVID-19 pandemic came from online surveys with extremely low or unreported response rates.

OBJECTIVE

To examine trend data in a calibrated screening for clinically significant anxiety and depression among adults in the only US government benchmark probability trend survey not disrupted by the COVID-19 pandemic.

DESIGN, SETTING, AND PARTICIPANTS

This survey study used the US Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance System (BRFSS), a monthly state-based trend survey conducted over the telephone. Participants were adult respondents in the 50 US states and District of Columbia who were surveyed March to December 2020 compared with the same months in 2017 to 2019.

EXPOSURES

Monthly state COVID-19 death rates.

MAIN OUTCOMES AND MEASURES

Estimated 30-day prevalence of clinically significant anxiety and depression based on responses to a single BRFSS item calibrated to a score of 6 or greater on the 4-item Patient Health Questionnaire (area under the receiver operating characteristic curve, 0.84). All percentages are weighted based on BRFSS calibration weights.

RESULTS

Overall, there were 1 429 354 respondents, with 1 093 663 in 2017 to 2019 (600 416 [51.1%] women; 87 153 [11.8%] non-Hispanic Black; 826 334 [61.5%] non-Hispanic White; 411 254 [27.8%] with college education; and 543 619 [56.8] employed) and 335 691 in 2020 (182 351 [51.3%] women; 25 517 [11.7%] non-Hispanic Black; 250 333 [60.5%] non-Hispanic White; 130 642 [29.3%] with college education; and 168 921 [54.9%] employed). Median within-state response rates were 45.9% to 49.4% in 2017 to 2019 and 47.9% in 2020. Estimated 30-day prevalence of clinically significant anxiety and depression was 0.4 (95% CI, 0.0 to 0.7) percentage points higher in March to December 2020 (12.4%) than March to December 2017 to 2019 (12.1%). This estimated increase was limited, however, to students (2.4 [95% CI, 0.8 to 3.9] percentage points) and the employed (0.9 [95% CI, 0.5 to 1.4] percentage points). Estimated prevalence decreased among the short-term unemployed (-1.8 [95% CI, -3.1 to -0.5] percentage points) and those unable to work (-4.2 [95% CI, -5.3 to -3.2] percentage points), but did not change significantly among the long-term unemployed (-2.1 [95% CI, -4.5 to 0.5] percentage points), homemakers (0.8 [95% CI, -0.3 to 1.9] percentage points), or the retired (0.1 [95% CI, -0.6 to 0.8] percentage points). The increase in anxiety and depression prevalence among employed people was positively associated with the state-month COVID-19 death rate (1.8 [95% CI, 1.2 to 2.5] percentage points when high and 0.0 [95% CI, -0.7 to 0.6] percentage points when low) and was elevated among women compared with men (2.0 [95% CI, 1.4 to 2.5] percentage points vs 0.2 [95% CI, -0.1 to 0.6] percentage points), Non-Hispanic White individuals compared with Hispanic and non-Hispanic Black individuals (1.3 [95% CI, 0.6 to 1.9] percentage points vs 1.1 [95% CI, -0.2 to 2.5] percentage points and 0.7 [95% CI, -0.1 to 1.5] percentage points), and those with college educations compared with less than high school educations (2.5 [95% CI, 1.9 to 3.1] percentage points vs -0.6 [95% CI, -2.7 to 1.4] percentage points).

CONCLUSIONS AND RELEVANCE

In this survey study, clinically significant US adult anxiety and depression increased less during 2020 than suggested by online surveys. However, this modest aggregate increase could mask more substantial increases in key population segments (eg, first responders) and might have become larger in 2021 and 2022.

Reducing racial/ethnic disparities in mental health service use among emerging adults: community-level supply factors

Objectives: Emerging adulthood-spanning 18-29 years of age-is associated with the highest risk for onset of certain behavioral health disorders (e.g. major depression, bipolar disorder, psychosis, substance use disorders) and high prevalence of many behavioral health disorders. Yet, rates of mental health service use remain low in this age range. Racial/ethnic minorities are particularly impacted by individual, cultural/linguistic, and community-level barriers to mental health care. This study examined community-level factors associated with mental health service use and investigated whether these associations varied by race/ethnicity.Design: This study analyzed individual- and county-level data for emerging adults in the United States (N=3,294) from the nationally representative Collaborative Psychiatric Epidemiological Surveys (CPES). Using the Andersen Model of Health Care Utilization, analyses examined predisposing, enabling, and need factors utilized in prior studies with adult samples as well as novel community characteristics hypothesized to impact service use among emerging adults of diverse racial/ethnic backgrounds. Past-year use of both specialty and any mental health services were assessed, controlling for individual- and community-level variables, and adjusting for presence of past-year mental health disorder, overall health status, and functional impairment. Differences between racial/ethnic minority groups and Non-Latino Whites were tested through a multilevel model incorporating random intercepts logistic regression, with analysis focusing on the interaction between race/ethnicity and community-level supply variables.Results: For past-year use of specialty mental health services, density of hospitals with child wellness programs was linked to service use among Black emerging adults, whereas density of hospitals with linguistic/translation services was linked to service use among Latino emerging adults.Conclusions: This study expands on previous research in behavioral health disparities to examine ways to improve behavioral health services for an emerging adult population with unmet service needs and identifies specific community-level factors that can improve mental health for racial/ethnic minority emerging adults.

Association of emotion reactivity and distress intolerance with suicide attempts in U.S. Army soldiers

INTRODUCTION

Emotion reactivity (ER) and distress intolerance (DI) may be associated with increased suicide attempt (SA) risk among U.S. Army soldiers.

METHOD

In this case-control study, 74 soldiers recently hospitalized for SA (cases) were compared with 133 control soldiers from the same Army installations selected based on either propensity score matching (n = 103) or reported 12-month suicide ideation (SI) (n = 30). Controls were weighted to represent the total Army population at the study sites and the subpopulation of 12-month ideators. Participants completed questionnaires assessing ER, DI, and other psychosocial variables. Logistic regression analyses examined whether ER and DI differentiated SA cases from the general population and from 12-month ideators before and after controlling for additional important risk factors (sociodemographic characteristics, stressors, mental disorders).

RESULTS

In univariate analyses, ER differentiated SA cases from both the general population (OR = 2.5[95%CI = 1.7-3.6]) and soldiers with 12-month SI (OR = 2.5[95%CI = 1.3-4.6]). DI also differentiated cases from the general population (OR = 2.9[95%CI = 2.0-4.1]) and 12-month ideators (OR = 1.9[95%CI = 1.1-3.5]). These associations persisted after controlling for sociodemographic variables, stressors, and mental disorders.

CONCLUSION

Findings provide evidence that higher ER and DI are associated with increased risk of SA among soldiers, even after adjusting for known risk factors. Prospective research with larger samples is needed.

Evaluating the heterogeneous effect of a modifiable risk factor on suicide: The case of vitamin D deficiency

OBJECTIVES

To illustrate the use of machine learning methods to search for heterogeneous effects of a target modifiable risk factor on suicide in observational studies. The illustration focuses on secondary analysis of a matched case-control study of vitamin D deficiency predicting subsequent suicide.

METHODS

We describe a variety of machine learning methods to search for prescriptive predictors; that is, predictors of significant variation in the association between a target risk factor and subsequent suicide. In each case, the purpose is to evaluate the potential value of selective intervention on the target risk factor to prevent the outcome based on the provisional assumption that the target risk factor is causal. The approaches illustrated include risk modeling based on the super learner ensemble machine learning method, Least Absolute Shrinkage and Selection Operator (Lasso) penalized regression, and the causal forest algorithm.

RESULTS

The logic of estimating heterogeneous intervention effects is exposited along with the illustration of some widely used methods for implementing this logic.

CONCLUSIONS

In addition to describing best practices in using the machine learning methods considered here, we close with a discussion of broader design and analysis issues in planning an observational study to investigate heterogeneous effects of a modifiable risk factor.

Predicting suicide attempts among U.S. Army soldiers after leaving active duty using information available before leaving active duty: results from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS)

Suicide risk is elevated among military service members who recently transitioned to civilian life. Identifying high-risk service members before this transition could facilitate provision of targeted preventive interventions. We investigated the feasibility of doing this by attempting to develop a prediction model for self-reported suicide attempts (SAs) after leaving or being released from active duty in the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS). This study included two self-report panel surveys (LS1: 2016-2018, LS2: 2018-2019) administered to respondents who previously participated while on active duty in one of three Army STARRS 2011-2014 baseline self-report surveys. We focus on respondents who left active duty >12 months before their LS survey (n = 8899). An ensemble machine learning model using predictors available prior to leaving active duty was developed in a 70% training sample and validated in a 30% test sample. The 12-month self-reported SA prevalence (SE) was 1.0% (0.1). Test sample AUC (SE) was 0.74 (0.06). The 15% of respondents with highest predicted risk included nearly two-thirds of 12-month SAs and over 80% of medically serious 12-month SAs. These results show that it is possible to identify soldiers at high post-transition self-report SA risk before the transition. Future model development is needed to examine prediction of SAs assessed by administrative data and using surveys administered closer to the time of leaving active duty.

The comparative importance of mental and physical disorders for health-related days out of role in the general population of Saudi Arabia

Background

A major component of illness burden is role impairment. As part of the recently-completed Saudi National Mental Health Survey (SNMHS), we compare the number of days out of role in the Saudi population associated with ten core mental disorders assessed in the survey to those associated with ten commonly occurring chronic physical disorders.

Methods

The SNMHS was a household survey that assessed prevalence of ten common anxiety, mood, disruptive behavior, and eating disorders in a nationally representative sample of n = 1981 citizens of the Kingdom of Saudi Arabia (KSA) ages 15–65. Comparison information was obtained on prevalence of ten common chronic physical disorders and number of health-related days out of role (DOR) in the 30 days before interview. Generalized linear models were used to examine univariate and multivariable associations of disorders with DOR and to calculate population attributable risk (PAR) separately and overall for the disorders controlling for socio-demographics.

Results

19.9% of respondents had one or more of the selected mental disorders and 47.1% had one or more of the selected physical disorders. Nine mental disorders and two physical disorders were associated with increased DOR. PAR was 32.9% for mental disorders, 27.0% for physical disorders, and 59.9% for both combined.

Conclusions

Mental disorders are associated with a substantial proportion of all health-related DOR in the Kingdom of Saudi Arabia. Programs to detect and treat mental disorders might lead to substantially decreased role impairment in the Kingdom.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-12721-z.

Risk of suicide attempt in reserve versus active component soldiers during deployment to the wars in Iraq and Afghanistan

INTRODUCTION

Little is known about the degree to which U.S. Army soldiers in the Reserve Components (Army National Guard and Army Reserve) and Active Component (Regular Army) differ with respect suicide attempt (SA) risk during high-stress times, such as deployment.

METHOD

Using administrative person-month records of enlisted soldiers on active duty during 2004-2009, we identified 1170 soldiers with a medically documented SA during deployment and an equal-probability control sample of other deployed soldiers (n = 52,828 person-months). Logistic regression analyses examined the association of Army component (Guard/Reserve vs. Regular) with SA before and after adjusting for socio-demographic and service-related predictors.

RESULTS

Guard/Reserve comprised 32.1% of enlisted soldiers and 19.7% of suicide attempters in-theater, with a SA rate of 81/100,000 person-years (vs. 157/100,000 person-years among Regular; rate ratio = 0.5 [95% CI = 0.5-0.6]). Risk peaked near mid-deployment for both groups but was consistently lower for Guard/Reserve throughout deployment. Guard/Reserve had lower odds of SA after adjusting for covariates (OR = 0.7 [95%CI = 0.6-0.8]). Predictors of SA were similar between components.

CONCLUSIONS

Guard/Reserve and Regular soldiers had similar patterns and predictors of SA during deployment, but Guard/Reserve had lower risk even after controlling for important risk factors. Additional research is needed to understand the lower SA risk among Guard/Reserve in-theater.

Perceived helpfulness of service sectors used for mental and substance use disorders: Findings from the WHO World Mental Health Surveys

BACKGROUND

Mental healthcare is delivered across service sectors that differ in level of specialization and intervention modalities typically offered. Little is known about the perceived helpfulness of the combinations of service sectors that patients use.

METHODS

Respondents 18 + years with 12-month DSM-IV mental or substance use disorders who saw a provider for mental health problems in the year before interview were identified from WHO World Mental Health surveys in 17 countries. Based upon the types of providers seen, patients were grouped into nine mutually exclusive single-sector or multi-sector 'treatment profiles'. Perceived helpfulness was defined as the patient's maximum rating of being helped ('a lot', 'some', 'a little' or 'not at all') of any type of provider seen in the profile. Logistic regression analysis was used to examine the joint associations of sociodemographics, disorder types, and treatment profiles with being helped 'a lot'.

RESULTS

Across all surveys combined, 29.4% (S.E. 0.6) of respondents with a 12-month disorder saw a provider in the past year (N = 3221). Of these patients, 58.2% (S.E. 1.0) reported being helped 'a lot'. Odds of being helped 'a lot' were significantly higher (odds ratios [ORs] = 1.50-1.89) among the 12.9% of patients who used specialized multi-sector profiles involving both psychiatrists and other mental health specialists, compared to other patients, despite their high comorbidities. Lower odds of being helped 'a lot' were found among patients who were seen only in the general medical, psychiatrist, or other mental health specialty sectors (ORs = 0.46-0.71). Female gender and older age were associated with increased odds of being helped 'a lot'. In models stratified by country income group, having 3 or more disorders (high-income countries only) and state-funded health insurance (low/middle-income countries only) were associated with increased odds of being helped 'a lot'.

CONCLUSIONS

Patients who received specialized, multi-sector care were more likely than other patients to report being helped 'a lot'. This result is consistent with previous research suggesting that persistence in help-seeking is associated with receiving helpful treatment. Given the nonrandom sorting of patients by types of providers seen and persistence in help-seeking, we cannot discount that selection bias may play some role in this pattern.

Prior histories of posttraumatic stress disorder and major depression and their onset and course in the three months after a motor vehicle collision in the AURORA study

BACKGROUND

A better understanding of the extent to which prior occurrences of posttraumatic stress disorder (PTSD) and major depressive episode (MDE) predict psychopathological reactions to subsequent traumas might be useful in targeting posttraumatic preventive interventions.

METHODS

Data come from 1306 patients presenting to 29 U.S. emergency departments (EDs) after a motor vehicle collision (MVC) in the advancing understanding of recovery after trauma study. Patients completed self-reports in the ED and 2-weeks, 8-weeks, and 3-months post-MVC. Associations of pre-MVC probable PTSD and probable MDE histories with subsequent 3-months post-MVC probable PTSD and probable MDE were examined along with mediation through intervening peritraumatic, 2-, and 8-week disorders.

RESULTS

27.6% of patients had 3-month post-MVC probable PTSD and/or MDE. Pre-MVC lifetime histories of these disorders were not only significant (relative risk = 2.6-7.4) but were dominant (63.1% population attributable risk proportion [PARP]) predictors of this 3-month outcome, with 46.6% prevalence of the outcome among patients with pre-MVC disorder histories versus 9.9% among those without such histories. The associations of pre-MVC lifetime disorders with the 3-month outcome were mediated largely by 2- and 8-week probable PTSD and MDE (PARP decreasing to 22.8% with controls for these intervening disorders). Decomposition showed that pre-MVC lifetime histories predicted both onset and persistence of these intervening disorders as well as the higher conditional prevalence of the 3-month outcome in the presence of these intervening disorders.

CONCLUSIONS

Assessments of pre-MVC PTSD and MDE histories and follow-ups at 2 and 8 weeks could help target early interventions for psychopathological reactions to MVCs.

The World Mental Health-International College Student (WMH-ICS) Survey in Canada: Protocol for a Mental Health and Substance Use Trend Study (Preprint)

Background

The World Health Organization World Mental Health International College Student (WMH-ICS) initiative aims to screen for mental health and substance use problems among postsecondary students on a global scale as well as to develop and evaluate evidence-based preventive and ameliorative interventions for this population. This protocol paper presents the Canadian version of the WMH-ICS survey, detailing the adapted survey instrument, the unique weekly cross-sectional administration, the multitiered recruitment strategy, and the associated risk mitigation protocols.

Objective

This paper aims to provide a methodological resource for researchers conducting cross-national comparisons of WMH-ICS data, as well as to serve as a useful guide for those interested in replicating the outlined cross-sectional methodology to better understand how mental health and substance use vary over time among university students.

Methods

The online survey is based on the WMH-ICS survey instrument, modified to the Canadian context by the addition of questions pertaining to Canadian-based guidelines and the translation of the survey to Canadian French. The survey is administered through the Qualtrics survey platform and is sent to an independent stratified random sample of 350 students per site weekly, followed by two reminder emails. Upon survey closure every week, a random subsample of 70 nonresponders are followed up with via phone or through a personal email in an effort to decrease nonresponder bias. The survey is accompanied by an extensive risk mitigation protocol that stratifies respondents by the level of need and provides tailored service recommendations, including a facilitated expedited appointment to student counseling services for those at increased risk of suicide. The anticipated sample size is approximately 5500 students per site per year.

Results

In February 2020, the Canadian survey was deployed at the University of British Columbia. This was followed by deployment at Simon Fraser University (November 2020), McMaster University (January 2021), and the University of Toronto (January 2022). Data collection at all 4 sites is ongoing. As of May 6, 2022, 29,503 responses have been collected.

Conclusions

Based on international collaboration, the Canadian version of the WMH-ICS survey incorporates a novel methodological approach centered on the weekly administration of a comprehensive cross-sectional survey to independent stratified random samples of university students. After 27 months of consecutive survey administration, we have developed and refined a survey protocol that has proven effective in engaging students at four Canadian institutions, allowing us to track how mental health and substance use vary over time using an internationally developed university student survey based on the criteria from the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition).

International Registered Report Identifier (IRRID)

RR1-10.2196/35168

Development and Validation of a Model to Predict Posttraumatic Stress Disorder and Major Depression After a Motor Vehicle Collision

IMPORTANCE

A substantial proportion of the 40 million people in the US who present to emergency departments (EDs) each year after traumatic events develop posttraumatic stress disorder (PTSD) or major depressive episode (MDE). Accurately identifying patients at high risk in the ED would facilitate the targeting of preventive interventions.

OBJECTIVES

To develop and validate a prediction tool based on ED reports after a motor vehicle collision to predict PTSD or MDE 3 months later.

DESIGN, SETTING, AND PARTICIPANTS

The Advancing Understanding of Recovery After Trauma (AURORA) study is a longitudinal study that examined adverse posttraumatic neuropsychiatric sequalae among patients who presented to 28 US urban EDs in the immediate aftermath of a traumatic experience. Enrollment began on September 25, 2017. The 1003 patients considered in this diagnostic/prognostic report completed 3-month assessments by January 31, 2020. Each patient received a baseline ED assessment along with follow-up self-report surveys 2 weeks, 8 weeks, and 3 months later. An ensemble machine learning method was used to predict 3-month PTSD or MDE from baseline information. Data analysis was performed from November 1, 2020, to May 31, 2021.

MAIN OUTCOMES AND MEASURES

The PTSD Checklist for DSM-5 was used to assess PTSD and the Patient Reported Outcomes Measurement Information System Depression Short-Form 8b to assess MDE.

RESULTS

A total of 1003 patients (median [interquartile range] age, 34.5 [24-43] years; 715 [weighted 67.9%] female; 100 [weighted 10.7%] Hispanic, 537 [weighted 52.7%] non-Hispanic Black, 324 [weighted 32.2%] non-Hispanic White, and 42 [weighted 4.4%] of non-Hispanic other race or ethnicity were included in this study. A total of 274 patients (weighted 26.6%) met criteria for 3-month PTSD or MDE. An ensemble machine learning model restricted to 30 predictors estimated in a training sample (patients from the Northeast or Midwest) had good prediction accuracy (mean [SE] area under the curve [AUC], 0.815 [0.031]) and calibration (mean [SE] integrated calibration index, 0.040 [0.002]; mean [SE] expected calibration error, 0.039 [0.002]) in an independent test sample (patients from the South). Patients in the top 30% of predicted risk accounted for 65% of all 3-month PTSD or MDE, with a mean (SE) positive predictive value of 58.2% (6.4%) among these patients at high risk. The model had good consistency across regions of the country in terms of both AUC (mean [SE], 0.789 [0.025] using the Northeast as the test sample and 0.809 [0.023] using the Midwest as the test sample) and calibration (mean [SE] integrated calibration index, 0.048 [0.003] using the Northeast as the test sample and 0.024 [0.001] using the Midwest as the test sample; mean [SE] expected calibration error, 0.034 [0.003] using the Northeast as the test sample and 0.025 [0.001] using the Midwest as the test sample). The most important predictors in terms of Shapley Additive Explanations values were symptoms of anxiety sensitivity and depressive disposition, psychological distress in the 30 days before motor vehicle collision, and peritraumatic psychosomatic symptoms.

CONCLUSIONS AND RELEVANCE

The results of this study suggest that a short set of questions feasible to administer in an ED can predict 3-month PTSD or MDE with good AUC, calibration, and geographic consistency. Patients at high risk can be identified in the ED for targeting if cost-effective preventive interventions are developed.

Predictors of Suicide Attempt Within 30 Days After First Medically Documented Suicidal Ideation in U.S. Army Soldiers

OBJECTIVE

The authors sought to identify predictors of imminent suicide attempt (within 30 days) among U.S. Army soldiers following their first documented suicidal ideation.

METHODS

Using administrative data from the Army Study to Assess Risk and Resilience in Servicemembers, the authors identified 11,178 active-duty Regular Army enlisted soldiers (2006-2009) with medically documented suicidal ideation and no prior medically documented suicide attempts. The authors examined risk factors for suicide attempt within 30 days of first suicidal ideation using logistic regression analyses, including sociodemographic and service-related characteristics, psychiatric diagnoses, physical health care visits, injuries, and history of family violence or crime perpetration or victimization.

RESULTS

Among soldiers with first documented suicidal ideation, 830 (7.4%) attempted suicide, 46.3% of whom (N=387) attempted suicide within 30 days (rate, 35.4 per 1,000 soldiers). Following a series of multivariate analyses, the final model identified females (odds ratio=1.3, 95% CI=1.0, 1.8), combat medics (odds ratio=1.6, 95% CI=1.1, 2.2), individuals with an anxiety disorder diagnosis prior to suicidal ideation (odds ratio=1.3, 95% CI=1.0, 1.6), and those who received a sleep disorder diagnosis on the same day as the recorded suicidal ideation (odds ratio=2.3, 95% CI=1.1, 4.6) as being more likely to attempt suicide within 30 days. Black soldiers (odds ratio=0.6, 95% CI=0.4, 0.9) and those who received an anxiety disorder diagnosis on the same day as suicidal ideation (odds ratio=0.7, 95% CI=0.5, 0.9) were less likely.

CONCLUSIONS

Suicide attempt risk is highest in the first 30 days following ideation diagnosis and is more likely among women, combat medics, and soldiers with an anxiety disorder diagnosis before suicidal ideation and a same-day sleep disorder diagnosis. Black soldiers and those with a same-day anxiety disorder diagnosis were at decreased risk. These factors may help identify soldiers at imminent risk of suicide attempt.

Mental Disorders, Gun Ownership, and Gun Carrying Among Soldiers After Leaving the Army, 2016-2019

Objectives. To examine associations of current mental and substance use disorders with self-reported gun ownership and carrying among recently separated US Army soldiers. Veterans have high rates of both gun ownership and mental disorders, the conjunction of which might contribute to the high suicide rate in this group. Methods. Cross-sectional survey data were collected in 2018-2019 from 5682 recently separated personnel who took part in the Army Study to Assess Risk and Resilience in Servicemembers. Validated measures assessed recent mood, anxiety, substance use, and externalizing disorders. Logistic regression models examined associations of sociodemographic characteristics, service characteristics, and mental disorders with gun ownership and carrying. Results. Of the participants, 50% reported gun ownership. About half of owners reported carrying some or most of the time. Mental disorders were not associated significantly with gun ownership. However, among gun owners, major depressive disorder, panic disorder, posttraumatic stress disorder, and intermittent explosive disorder were associated with significantly elevated odds of carrying at least some of the time. Conclusions. Mental disorders are not associated with gun ownership among recently separated Army personnel, but some mental disorders are associated with carrying among gun owners. (Am J Public Health. 2021;111(10):1855-1864. https://doi.org/10.2105/AJPH.2021.306420).

Conducting a state-of-the-art mental health survey in a traditional setting: Challenges and lessons from piloting the World Mental Health Survey in Qatar

OBJECTIVES

A small country in the Arabian Peninsula, Qatar experienced rapid economic growth in the last 3 decades accompanied by major socio-demographic shifts towards a younger and more highly educated population. To date, no national epidemiological study has examined the prevalence, associated factors, or sequelae of mental disorders in Qatar's general population.

METHODS

The World Mental Health Qatar (WMHQ) is a national mental health needs assessment survey and is the first carried out in collaboration with the World Mental Health Survey initiative to assess the prevalence and burden of psychiatric illnesses among the full Arabic speaking population (nationals and non-nationals) within the same country.

RESULTS

Standard translation and harmonization procedures were used to develop the WMHQ instrument. A survey quality control system with standard performance indicators was developed to ensure interviewer adherence to standard practices. A pilot study was then carried out just prior to the COVID-19 pandemic. Endorsement from public health authorities and sequential revision of the interview schedule led to full survey completion (as opposed to partial completion) and good overall response rate.

CONCLUSIONS

The WMHQ survey will provide timely and actionable information based on quality enhancement procedures put in place during the development and piloting of the study.

Patterns of care and dropout rates from outpatient mental healthcare in low-, middle- and high-income countries from the World Health Organization's World Mental Health Survey Initiative

BACKGROUND

There is a substantial proportion of patients who drop out of treatment before they receive minimally adequate care. They tend to have worse health outcomes than those who complete treatment. Our main goal is to describe the frequency and determinants of dropout from treatment for mental disorders in low-, middle-, and high-income countries.

METHODS

Respondents from 13 low- or middle-income countries (N = 60 224) and 15 in high-income countries (N = 77 303) were screened for mental and substance use disorders. Cross-tabulations were used to examine the distribution of treatment and dropout rates for those who screened positive. The timing of dropout was examined using Kaplan-Meier curves. Predictors of dropout were examined with survival analysis using a logistic link function.

RESULTS

Dropout rates are high, both in high-income (30%) and low/middle-income (45%) countries. Dropout mostly occurs during the first two visits. It is higher in general medical rather than in specialist settings (nearly 60% v. 20% in lower income settings). It is also higher for mild and moderate than for severe presentations. The lack of financial protection for mental health services is associated with overall increased dropout from care.

CONCLUSIONS

Extending financial protection and coverage for mental disorders may reduce dropout. Efficiency can be improved by managing the milder clinical presentations at the entry point to the mental health system, providing adequate training, support and specialist supervision for non-specialists, and streamlining referral to psychiatrists for more severe cases.

Perceived helpfulness of treatment for generalized anxiety disorder: a World Mental Health Surveys report

BACKGROUND

Treatment guidelines for generalized anxiety disorder (GAD) are based on a relatively small number of randomized controlled trials and do not consider patient-centered perceptions of treatment helpfulness. We investigated the prevalence and predictors of patient-reported treatment helpfulness for DSM-5 GAD and its two main treatment pathways: encounter-level treatment helpfulness and persistence in help-seeking after prior unhelpful treatment.

METHODS

Data came from community epidemiologic surveys in 23 countries in the WHO World Mental Health surveys. DSM-5 GAD was assessed with the fully structured WHO Composite International Diagnostic Interview Version 3.0. Respondents with a history of GAD were asked whether they ever received treatment and, if so, whether they ever considered this treatment helpful. Number of professionals seen before obtaining helpful treatment was also assessed. Parallel survival models estimated probability and predictors of a given treatment being perceived as helpful and of persisting in help-seeking after prior unhelpful treatment.

RESULTS

The overall prevalence rate of GAD was 4.5%, with lower prevalence in low/middle-income countries (2.8%) than high-income countries (5.3%); 34.6% of respondents with lifetime GAD reported ever obtaining treatment for their GAD, with lower proportions in low/middle-income countries (19.2%) than high-income countries (38.4%); 3) 70% of those who received treatment perceived the treatment to be helpful, with prevalence comparable in low/middle-income countries and high-income countries. Survival analysis suggested that virtually all patients would have obtained helpful treatment if they had persisted in help-seeking with up to 10 professionals. However, we estimated that only 29.7% of patients would have persisted that long. Obtaining helpful treatment at the person-level was associated with treatment type, comorbid panic/agoraphobia, and childhood adversities, but most of these predictors were important because they predicted persistence rather than encounter-level treatment helpfulness.

CONCLUSIONS

The majority of individuals with GAD do not receive treatment. Most of those who receive treatment regard it as helpful, but receiving helpful treatment typically requires persistence in help-seeking. Future research should focus on ensuring that helpfulness is included as part of the evaluation. Clinicians need to emphasize the importance of persistence to patients beginning treatment.